------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\brdbl\Dropbox\New Alliance Work\Burden-Sharing Survey\Submissions\Final Versions\Replication Package\Replicati
> on_LogFile.log
  log type:  text
 opened on:  22 Nov 2023, 15:01:16

. do "C:\Users\brdbl\AppData\Local\Temp\STD1d04_000000.tmp"

. clear

. use ReplicationData.dta

. 
. *Figure 1a*
. preserve

. label var treatment_abandon "Unconditional Abandonment"

. label var treatment_reassurance "Unconditional Reassurance"

. label var treatment_conditional "Conditional Pressure"

. label var treatment_domestic "Domestic Pressure"

. label var treatment_normative "Appeal to Obligations"

. label var treatment_shaming "Shaming"

. reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatment_sh
> aming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      4.86
       Model |  43.8146422         7  6.25923461   Prob > F        =    0.0000
    Residual |  5124.30932     3,977  1.28848613   R-squared       =    0.0085
-------------+----------------------------------   Adj R-squared   =    0.0067
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1351

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .1012542   .0648405     1.56   0.118    -.0258695    .2283779
    treatment_abandon |   .1660634    .064868     2.56   0.011     .0388858    .2932409
treatment_conditional |    .237753   .0645489     3.68   0.000     .1112009    .3643051
   treatment_domestic |   .0263072    .064681     0.41   0.684    -.1005038    .1531182
  treatment_normative |   .0622068   .0646535     0.96   0.336    -.0645504     .188964
    treatment_shaming |   .0202447   .0813143     0.25   0.803    -.1391769    .1796662
           country_id |  -.1208644   .0374403    -3.23   0.001    -.1942683   -.0474606
                _cons |   3.535685   .0493499    71.65   0.000     3.438931    3.632438
---------------------------------------------------------------------------------------

. estimates store base

. reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatment_sh
> aming female age education polawareness country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(11, 3973)     =     19.89
       Model |  269.773438        11   24.524858   Prob > F        =    0.0000
    Residual |  4898.35053     3,973  1.23290977   R-squared       =    0.0522
-------------+----------------------------------   Adj R-squared   =    0.0496
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1104

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0916998   .0634415     1.45   0.148    -.0326812    .2160808
    treatment_abandon |   .1589662   .0634956     2.50   0.012     .0344792    .2834532
treatment_conditional |   .2255226   .0631694     3.57   0.000     .1016751    .3493702
   treatment_domestic |   .0290492   .0632892     0.46   0.646    -.0950332    .1531316
  treatment_normative |   .0489205   .0632601     0.77   0.439    -.0751048    .1729458
    treatment_shaming |   .0040179   .0795598     0.05   0.960     -.151964    .1599998
               female |  -.0132117   .0354497    -0.37   0.709     -.082713    .0562896
                  age |   .0107929   .0011645     9.27   0.000     .0085098     .013076
            education |    .006804   .0123053     0.55   0.580    -.0173213    .0309293
         polawareness |   .1457816   .0210766     6.92   0.000     .1044597    .1871035
           country_id |  -.1822863   .0371309    -4.91   0.000    -.2550836   -.1094889
                _cons |   2.589697   .0993107    26.08   0.000     2.394992    2.784402
---------------------------------------------------------------------------------------

. estimates store controls

. coefplot (base, label(Baseline)) (controls, label(With Controls) msymbol(triangle) ciopts(lpattern(dash_dot))) ///
> || , drop(_cons ) graphregion(fcolor(white)) xline(0) order(treatment_reassurance treatment_abandon treatment_conditional treatmen
> t_domestic treatment_normative treatment_shaming country_id female age education polawareness)  scheme(white_tableau)

. *graph export "Figure1a.jpg", replace
. eststo clear

. restore

. 
. *Figure 1b*
. preserve

. label var treatment_abandon "Unconditional Abandonment"

. label var treatment_reassurance "Unconditional Reassurance"

. label var treatment_conditional "Conditional Pressure"

. label var treatment_domestic "Domestic Pressure"

. label var treatment_normative "Appeal to Obligations"

. label var treatment_shaming "Shaming"

. reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatment_sh
> aming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      4.86
       Model |  43.8146422         7  6.25923461   Prob > F        =    0.0000
    Residual |  5124.30932     3,977  1.28848613   R-squared       =    0.0085
-------------+----------------------------------   Adj R-squared   =    0.0067
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1351

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .1012542   .0648405     1.56   0.118    -.0258695    .2283779
    treatment_abandon |   .1660634    .064868     2.56   0.011     .0388858    .2932409
treatment_conditional |    .237753   .0645489     3.68   0.000     .1112009    .3643051
   treatment_domestic |   .0263072    .064681     0.41   0.684    -.1005038    .1531182
  treatment_normative |   .0622068   .0646535     0.96   0.336    -.0645504     .188964
    treatment_shaming |   .0202447   .0813143     0.25   0.803    -.1391769    .1796662
           country_id |  -.1208644   .0374403    -3.23   0.001    -.1942683   -.0474606
                _cons |   3.535685   .0493499    71.65   0.000     3.438931    3.632438
---------------------------------------------------------------------------------------

. estimates store full

. reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative if country==
> "Poland"

      Source |       SS           df       MS      Number of obs   =     1,848
-------------+----------------------------------   F(5, 1842)      =      2.02
       Model |  14.6837122         5  2.93674244   Prob > F        =    0.0732
    Residual |  2679.76596     1,842  1.45481323   R-squared       =    0.0054
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  2694.44968     1,847  1.45882495   Root MSE        =    1.2062

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0531442    .097514     0.54   0.586    -.1381055    .2443939
    treatment_abandon |   .1767252   .0973535     1.82   0.070    -.0142097    .3676601
treatment_conditional |   .2527056   .0968828     2.61   0.009     .0626939    .4427173
   treatment_domestic |   .0526788   .0969602     0.54   0.587    -.1374846    .2428422
  treatment_normative |   .0375862    .097274     0.39   0.699    -.1531926     .228365
                _cons |   3.538961   .0687271    51.49   0.000      3.40417    3.673752
---------------------------------------------------------------------------------------

. estimates store poland

. reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatment_sh
> aming if country=="Germany"

      Source |       SS           df       MS      Number of obs   =     2,137
-------------+----------------------------------   F(6, 2130)      =      2.05
       Model |  14.0919544         6  2.34865906   Prob > F        =    0.0563
    Residual |  2442.14857     2,130  1.14654862   R-squared       =    0.0057
-------------+----------------------------------   Adj R-squared   =    0.0029
       Total |  2456.24052     2,136  1.14992534   Root MSE        =    1.0708

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .1494805   .0864329     1.73   0.084    -.0200211    .3189822
    treatment_abandon |   .1550911   .0866515     1.79   0.074    -.0148393    .3250215
treatment_conditional |   .2224114    .086218     2.58   0.010     .0533311    .3914916
   treatment_domestic |  -.0009795   .0865053    -0.01   0.991    -.1706232    .1686642
  treatment_normative |   .0867958   .0861472     1.01   0.314    -.0821456    .2557372
    treatment_shaming |   .0234894   .0860768     0.27   0.785    -.1453139    .1922927
                _cons |   3.411576   .0607178    56.19   0.000     3.292503    3.530648
---------------------------------------------------------------------------------------

. estimates store germany

. coefplot (full, label(Full Sample)) (poland, label(Poland) msymbol(diamond) ciopts(lpattern(dot))) (germany, label(Germany) msymbo
> l(square) ciopts(lpattern(dash))) ///
> || , drop(_cons ) graphregion(fcolor(white)) xtick(-0.4(0.2)0.4) xlabel(-0.4(0.2)0.4) xline(0) order(treatment_reassurance treatme
> nt_abandon treatment_conditional treatment_domestic treatment_normative treatment_shaming country_id) scheme(white_tableau) 

. *graph export "Figure1b.jpg", replace
. eststo clear

. restore

. 
. *Figure 2a*
. preserve

. eststo clear

. reg defensespend i.treatment_reassurance##c.threatperception_pretreat i.treatment_abandon##c.threatperception_pretreat i.treatment
> _conditional##c.threatperception_pretreat i.treatment_domestic##c.threatperception_pretreat i.treatment_normative##c.threatpercept
> ion_pretreat country_id
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(12, 3972)     =      3.72
       Model |  57.4498319        12  4.78748599   Prob > F        =    0.0000
    Residual |  5110.67413     3,972  1.28667526   R-squared       =    0.0111
-------------+----------------------------------   Adj R-squared   =    0.0081
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1343

-------------------------------------------------------------------------------------------------------------------
                                     defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------------------------------------+----------------------------------------------------------------
                          1.treatment_reassurance |  -.2756065    .223116    -1.24   0.217    -.7130391    .1618261
                        threatperception_pretreat |  -.1066444   .0443438    -2.40   0.016     -.193583   -.0197057
                                                  |
treatment_reassurance#c.threatperception_pretreat |
                                               1  |   .1275938    .073162     1.74   0.081    -.0158447    .2710324
                                                  |
                              1.treatment_abandon |  -.2690819   .2286875    -1.18   0.239    -.7174377    .1792739
                        threatperception_pretreat |          0  (omitted)
                                                  |
    treatment_abandon#c.threatperception_pretreat |
                                               1  |   .1462733   .0738684     1.98   0.048     .0014498    .2910967
                                                  |
                          1.treatment_conditional |  -.2252369   .2146605    -1.05   0.294    -.6460919    .1956181
                        threatperception_pretreat |          0  (omitted)
                                                  |
treatment_conditional#c.threatperception_pretreat |
                                               1  |   .1558568   .0695208     2.24   0.025      .019557    .2921566
                                                  |
                             1.treatment_domestic |  -.5754132   .2245613    -2.56   0.010    -1.015679   -.1351471
                        threatperception_pretreat |          0  (omitted)
                                                  |
   treatment_domestic#c.threatperception_pretreat |
                                               1  |   .2037853   .0737932     2.76   0.006     .0591092    .3484615
                                                  |
                            1.treatment_normative |  -.3869171   .2124049    -1.82   0.069    -.8033498    .0295157
                        threatperception_pretreat |          0  (omitted)
                                                  |
  treatment_normative#c.threatperception_pretreat |
                                               1  |    .151275   .0687574     2.20   0.028     .0164719    .2860782
                                                  |
                                       country_id |  -.1125486   .0377903    -2.98   0.003    -.1866389   -.0384583
                                            _cons |   3.846322   .1392425    27.62   0.000     3.573329    4.119316
-------------------------------------------------------------------------------------------------------------------

. eststo M

. listcoef, help //returns the coeficients; "help listcoef" to learn 

regress (N=3985): Unstandardized and Standardized Estimates 

 Observed SD: 1.1389556
 SD of Error: 1.1343171

---------------------------------------------------------------------------
defensespend|      b         t     P>|t|    bStdX    bStdY   bStdXY      SDofX
---------+-----------------------------------------------------------------
1.treatment_reassurance|  -0.27561   -1.235   0.217  -0.0990  -0.2420  -0.0870     0.3594
threatperception_pretreat|  -0.10664   -2.405   0.016  -0.0876  -0.0936  -0.0769     0.8214
1.treatment_reassurance#c.threatperception_pretreat|   0.12759    1.744   0.081   0.1414   0.1120   0.1242     1.1083
1.treatment_abandon|  -0.26908   -1.177   0.239  -0.0966  -0.2363  -0.0848     0.3591
1.treatment_abandon#c.threatperception_pretreat|   0.14627    1.980   0.048   0.1656   0.1284   0.1454     1.1323
1.treatment_conditional|  -0.22524   -1.049   0.294  -0.0815  -0.1978  -0.0716     0.3620
1.treatment_conditional#c.threatperception_pretreat|   0.15586    2.242   0.025   0.1777   0.1368   0.1561     1.1404
1.treatment_domestic|  -0.57541   -2.562   0.010  -0.2076  -0.5052  -0.1823     0.3608
1.treatment_domestic#c.threatperception_pretreat|   0.20379    2.762   0.006   0.2259   0.1789   0.1983     1.1083
1.treatment_normative|  -0.38692   -1.822   0.069  -0.1397  -0.3397  -0.1227     0.3611
1.treatment_normative#c.threatperception_pretreat|   0.15128    2.200   0.028   0.1723   0.1328   0.1512     1.1387
country_id|  -0.11255   -2.978   0.003  -0.0561  -0.0988  -0.0493     0.4987
---------------------------------------------------------------------------
       b = raw coefficient
       t = t-score for test of b=0
   P>|t| = p-value for t-test
   bStdX = x-standardized coefficient
   bStdY = y-standardized coefficient
  bStdXY = fully standardized coefficient
   SDofX = standard deviation of X

. //now the margins
. estimates restore M
(results M are active now)

. margins, dydx(treatment_domestic) at(threatperception_pretreat=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_domestic

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

---------------------------------------------------------------------------------------
                      |      dy/dx  Legend
----------------------+----------------------------------------------------------------
0.treatment_domestic  |  (base outcome)
----------------------+----------------------------------------------------------------
1.treatment_domestic  |
                  _at |
                   1  |  -.3716279  _b[1.treatment_domestic:1bn._at]
                   2  |  -.1678425  _b[1.treatment_domestic:2._at]
                   3  |   .0359428  _b[1.treatment_domestic:3._at]
                   4  |   .2397281  _b[1.treatment_domestic:4._at]
                   5  |   .4435135  _b[1.treatment_domestic:5._at]
---------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store domestic

. estimates restore M
(results M are active now)

. margins, dydx(treatment_abandon) at(threatperception_pretreat=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_abandon

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

--------------------------------------------------------------------------------------
                     |      dy/dx  Legend
---------------------+----------------------------------------------------------------
0.treatment_abandon  |  (base outcome)
---------------------+----------------------------------------------------------------
1.treatment_abandon  |
                 _at |
                  1  |  -.1228087  _b[1.treatment_abandon:1bn._at]
                  2  |   .0234646  _b[1.treatment_abandon:2._at]
                  3  |   .1697379  _b[1.treatment_abandon:3._at]
                  4  |   .3160111  _b[1.treatment_abandon:4._at]
                  5  |   .4622844  _b[1.treatment_abandon:5._at]
--------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store abandon

. estimates restore M
(results M are active now)

. margins, dydx(treatment_conditional) at(threatperception_pretreat=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_conditional

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_conditional  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_conditional  |
                     _at |
                      1  |  -.0693801  _b[1.treatment_conditional:1bn._at]
                      2  |   .0864767  _b[1.treatment_conditional:2._at]
                      3  |   .2423336  _b[1.treatment_conditional:3._at]
                      4  |   .3981904  _b[1.treatment_conditional:4._at]
                      5  |   .5540472  _b[1.treatment_conditional:5._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store conditional

. est restore M
(results M are active now)

. margins, dydx(treatment_reassurance) at(threatperception_pretreat=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_reassurance

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               threatperc~t    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_reassurance  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_reassurance  |
                     _at |
                      1  |  -.1480126  _b[1.treatment_reassurance:1bn._at]
                      2  |  -.0204188  _b[1.treatment_reassurance:2._at]
                      3  |    .107175  _b[1.treatment_reassurance:3._at]
                      4  |   .2347689  _b[1.treatment_reassurance:4._at]
                      5  |   .3623627  _b[1.treatment_reassurance:5._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store reassurance

. 
. coefplot (reassurance, offset(-0.33)) (abandon, offset(-0.16)) (conditional, offset(0)) (domestic, offset(0.16)), ///
> recast(bar) barw(0.15) vertical ylab(0(.1).7) ///
> ciopts(recast(rcap) color(black%50)) citop ///
> legend(order(1 "Reassurance" 3 "Abandonment" ///
> 5 "Conditional Pressure" 7 "Domestic Pressure")) ///
> ytitle("Treatment Effects") ///
> xtitle("Threat perception (pre-treatment)")  ///
> xlabel(1(1)5) ytick(-1(0.2)1) ylabel(-1(0.2)1) graphregion(fcolor(white)) yline(0, lpattern(dash) lstyle(foreground) lcolor(black)
> ) scheme(white_tableau)

. *graph export "Figure2a.jpg", replace
. eststo clear

. restore

. 
. 
. 
. *Figure 2b*
. preserve

. eststo clear

. reg defensespend i.treatment_reassurance##c.usconfidence i.treatment_abandon##c.usconfidence i.treatment_conditional##c.usconfiden
> ce i.treatment_domestic##c.usconfidence i.treatment_normative##c.usconfidence country_id
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(12, 3972)     =     18.65
       Model |  275.618874        12  22.9682395   Prob > F        =    0.0000
    Residual |  4892.50509     3,972  1.23174851   R-squared       =    0.0533
-------------+----------------------------------   Adj R-squared   =    0.0505
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1098

------------------------------------------------------------------------------------------------------
                        defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------------+----------------------------------------------------------------
             1.treatment_reassurance |    .010246   .1599608     0.06   0.949     -.303367     .323859
                        usconfidence |    .208232   .0322931     6.45   0.000     .1449195    .2715445
                                     |
treatment_reassurance#c.usconfidence |
                                  1  |   .0279575   .0529528     0.53   0.598    -.0758597    .1317748
                                     |
                 1.treatment_abandon |    .207956   .1621096     1.28   0.200    -.1098699    .5257819
                        usconfidence |          0  (omitted)
                                     |
    treatment_abandon#c.usconfidence |
                                  1  |  -.0220671   .0532232    -0.41   0.678    -.1264144    .0822803
                                     |
             1.treatment_conditional |   .2883344   .1561368     1.85   0.065    -.0177813    .5944501
                        usconfidence |          0  (omitted)
                                     |
treatment_conditional#c.usconfidence |
                                  1  |  -.0242516   .0512444    -0.47   0.636    -.1247195    .0762162
                                     |
                1.treatment_domestic |  -.1166915   .1611257    -0.72   0.469    -.4325883    .1992053
                        usconfidence |          0  (omitted)
                                     |
   treatment_domestic#c.usconfidence |
                                  1  |   .0448709   .0532341     0.84   0.399    -.0594978    .1492395
                                     |
               1.treatment_normative |  -.0730303   .1556468    -0.47   0.639    -.3781854    .2321248
                        usconfidence |          0  (omitted)
                                     |
  treatment_normative#c.usconfidence |
                                  1  |   .0440886   .0514032     0.86   0.391    -.0566906    .1448678
                                     |
                          country_id |  -.1585697   .0357821    -4.43   0.000    -.2287228   -.0884166
                               _cons |   2.981304   .0998726    29.85   0.000     2.785498    3.177111
------------------------------------------------------------------------------------------------------

. eststo M

. listcoef, help //returns the coeficients; "help listcoef" to learn 

regress (N=3985): Unstandardized and Standardized Estimates 

 Observed SD: 1.1389556
 SD of Error: 1.1098417

---------------------------------------------------------------------------
defensespend|      b         t     P>|t|    bStdX    bStdY   bStdXY      SDofX
---------+-----------------------------------------------------------------
1.treatment_reassurance|   0.01025    0.064   0.949   0.0037   0.0090   0.0032     0.3594
usconfidence|   0.20823    6.448   0.000   0.2287   0.1828   0.2008     1.0982
1.treatment_reassurance#c.usconfidence|   0.02796    0.528   0.598   0.0306   0.0245   0.0269     1.0940
1.treatment_abandon|   0.20796    1.283   0.200   0.0747   0.1826   0.0656     0.3591
1.treatment_abandon#c.usconfidence|  -0.02207   -0.415   0.678  -0.0244  -0.0194  -0.0214     1.1057
1.treatment_conditional|   0.28833    1.847   0.065   0.1044   0.2532   0.0916     0.3620
1.treatment_conditional#c.usconfidence|  -0.02425   -0.473   0.636  -0.0271  -0.0213  -0.0238     1.1189
1.treatment_domestic|  -0.11669   -0.724   0.469  -0.0421  -0.1025  -0.0370     0.3608
1.treatment_domestic#c.usconfidence|   0.04487    0.843   0.399   0.0494   0.0394   0.0434     1.1019
1.treatment_normative|  -0.07303   -0.469   0.639  -0.0264  -0.0641  -0.0232     0.3611
1.treatment_normative#c.usconfidence|   0.04409    0.858   0.391   0.0487   0.0387   0.0428     1.1050
country_id|  -0.15857   -4.432   0.000  -0.0791  -0.1392  -0.0694     0.4987
---------------------------------------------------------------------------
       b = raw coefficient
       t = t-score for test of b=0
   P>|t| = p-value for t-test
   bStdX = x-standardized coefficient
   bStdY = y-standardized coefficient
  bStdXY = fully standardized coefficient
   SDofX = standard deviation of X

. //now the margins
. estimates restore M
(results M are active now)

. margins, dydx(treatment_domestic) at(usconfidence=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_domestic

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

---------------------------------------------------------------------------------------
                      |      dy/dx  Legend
----------------------+----------------------------------------------------------------
0.treatment_domestic  |  (base outcome)
----------------------+----------------------------------------------------------------
1.treatment_domestic  |
                  _at |
                   1  |  -.0718206  _b[1.treatment_domestic:1bn._at]
                   2  |  -.0269497  _b[1.treatment_domestic:2._at]
                   3  |   .0179211  _b[1.treatment_domestic:3._at]
                   4  |    .062792  _b[1.treatment_domestic:4._at]
                   5  |   .1076628  _b[1.treatment_domestic:5._at]
---------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store domestic

. estimates restore M
(results M are active now)

. margins, dydx(treatment_abandon) at(usconfidence=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_abandon

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

--------------------------------------------------------------------------------------
                     |      dy/dx  Legend
---------------------+----------------------------------------------------------------
0.treatment_abandon  |  (base outcome)
---------------------+----------------------------------------------------------------
1.treatment_abandon  |
                 _at |
                  1  |   .1858889  _b[1.treatment_abandon:1bn._at]
                  2  |   .1638218  _b[1.treatment_abandon:2._at]
                  3  |   .1417548  _b[1.treatment_abandon:3._at]
                  4  |   .1196877  _b[1.treatment_abandon:4._at]
                  5  |   .0976206  _b[1.treatment_abandon:5._at]
--------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store abandon

. estimates restore M
(results M are active now)

. margins, dydx(treatment_conditional) at(usconfidence=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_conditional

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_conditional  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_conditional  |
                     _at |
                      1  |   .2640828  _b[1.treatment_conditional:1bn._at]
                      2  |   .2398312  _b[1.treatment_conditional:2._at]
                      3  |   .2155796  _b[1.treatment_conditional:3._at]
                      4  |    .191328  _b[1.treatment_conditional:4._at]
                      5  |   .1670764  _b[1.treatment_conditional:5._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store conditional

. est restore M
(results M are active now)

. margins, dydx(treatment_reassurance) at(usconfidence=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_reassurance

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               usconfidence    =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_reassurance  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_reassurance  |
                     _at |
                      1  |   .0382036  _b[1.treatment_reassurance:1bn._at]
                      2  |   .0661611  _b[1.treatment_reassurance:2._at]
                      3  |   .0941186  _b[1.treatment_reassurance:3._at]
                      4  |   .1220762  _b[1.treatment_reassurance:4._at]
                      5  |   .1500337  _b[1.treatment_reassurance:5._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store reassurance

. 
. coefplot (reassurance, offset(-0.33)) (abandon, offset(-0.16)) (conditional, offset(0)) (domestic, offset(0.16)), ///
> recast(bar) barw(0.15) vertical ylab(0(.1).7) ///
> ciopts(recast(rcap) color(black%50)) citop ///
> legend(order(1 "Reassurance" 3 "Abandonment" ///
> 5 "Conditional Pressure" 7 "Domestic Pressure")) ///
> ytitle("Treatment Effects") ///
> xtitle("Confidence in the US (pre-treatment)")  ///
> xlabel(1(1)5) ytick(-1(0.2)1) ylabel(-1(0.2)1) graphregion(fcolor(white)) yline(0, lpattern(dash) lstyle(foreground) lcolor(black)
> ) scheme(white_tableau)

. *graph export "Figure2b.jpg", replace
. eststo clear

. restore

. 
. 
. *Figure 3*
. preserve

. eststo clear

. label var treatment_abandon "Unconditional Abandonment"

. label var treatment_reassurance "Unconditional Reassurance"

. label var treatment_conditional "Conditional Pressure"

. label var treatment_domestic "Domestic Pressure"

. label var treatment_normative "Appeal to Obligations"

. label var treatment_shaming "Shaming"

. eststo: reg moralobligation treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative t
> reatment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      5.81
       Model |   15.520742         7  2.21724886   Prob > F        =    0.0000
    Residual |  1518.89231     3,977  .381919112   R-squared       =    0.0101
-------------+----------------------------------   Adj R-squared   =    0.0084
       Total |  1534.41305     3,984  .385143838   Root MSE        =      .618

---------------------------------------------------------------------------------------
      moralobligation |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0858488   .0353014     2.43   0.015     .0166383    .1550594
    treatment_abandon |   -.028828   .0353164    -0.82   0.414    -.0980679    .0404119
treatment_conditional |   .0270238   .0351427     0.77   0.442    -.0418756    .0959231
   treatment_domestic |   .0163244   .0352146     0.46   0.643    -.0527159    .0853647
  treatment_normative |   .0265573   .0351996     0.75   0.451    -.0424538    .0955683
    treatment_shaming |   .0571263   .0442703     1.29   0.197    -.0296684    .1439209
           country_id |   -.109649   .0203838    -5.38   0.000    -.1496126   -.0696854
                _cons |   2.248951   .0268678    83.70   0.000     2.196275    2.301627
---------------------------------------------------------------------------------------
(est1 stored)

. estimates store moral

. eststo: reg confidence_us treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative tre
> atment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      8.33
       Model |   69.016613         7  9.85951615   Prob > F        =    0.0000
    Residual |  4708.71388     3,977  1.18398639   R-squared       =    0.0144
-------------+----------------------------------   Adj R-squared   =    0.0127
       Total |  4777.73049     3,984  1.19922954   Root MSE        =    1.0881

---------------------------------------------------------------------------------------
        confidence_us |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0085119   .0621555    -0.14   0.891    -.1303715    .1133478
    treatment_abandon |   .2813273   .0621819     4.52   0.000      .159416    .4032386
treatment_conditional |   .0992943    .061876     1.60   0.109    -.0220175     .220606
   treatment_domestic |   .1699815   .0620026     2.74   0.006     .0484216    .2915414
  treatment_normative |   .0111316   .0619763     0.18   0.857    -.1103767      .13264
    treatment_shaming |  -.0129176   .0779472    -0.17   0.868    -.1657377    .1399026
           country_id |  -.1435976   .0358899    -4.00   0.000    -.2139619   -.0732333
                _cons |    3.08184   .0473063    65.15   0.000     2.989093    3.174587
---------------------------------------------------------------------------------------
(est2 stored)

. estimates store confidence

. eststo: reg threatperception treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative 
> treatment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      2.54
       Model |  21.2863156         7  3.04090223   Prob > F        =    0.0131
    Residual |  4756.49637     3,977   1.1960011   R-squared       =    0.0045
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  4777.78269     3,984  1.19924264   Root MSE        =    1.0936

---------------------------------------------------------------------------------------
     threatperception |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0424974   .0624701    -0.68   0.496    -.1649738     .079979
    treatment_abandon |   .1438111   .0624966     2.30   0.021     .0212828    .2663394
treatment_conditional |   .0567936   .0621892     0.91   0.361    -.0651321    .1787193
   treatment_domestic |   .0146566   .0623164     0.24   0.814    -.1075186    .1368317
  treatment_normative |   .0144723     .06229     0.23   0.816     -.107651    .1365956
    treatment_shaming |  -.1204236   .0783417    -1.54   0.124    -.2740171      .03317
           country_id |   .0764884   .0360715     2.12   0.034      .005768    .1472088
                _cons |   2.716013   .0475458    57.12   0.000     2.622797    2.809229
---------------------------------------------------------------------------------------
(est3 stored)

. estimates store threat

. eststo: reg reactance treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatme
> nt_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =     18.03
       Model |   469.52506         7  67.0750086   Prob > F        =    0.0000
    Residual |  14798.4339     3,977  3.72100425   R-squared       =    0.0308
-------------+----------------------------------   Adj R-squared   =    0.0290
       Total |   15267.959     3,984  3.83231902   Root MSE        =     1.929

---------------------------------------------------------------------------------------
            reactance |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0796294   .1101885     0.72   0.470    -.1364019    .2956607
    treatment_abandon |   .7935384   .1102352     7.20   0.000     .5774155    1.009661
treatment_conditional |   .3711216   .1096931     3.38   0.001     .1560616    .5861815
   treatment_domestic |   .5679892   .1099175     5.17   0.000     .3524893    .7834891
  treatment_normative |   .0331014   .1098709     0.30   0.763    -.1823071    .2485099
    treatment_shaming |   .0956643   .1381838     0.69   0.489    -.1752533     .366582
           country_id |   .4019692   .0636252     6.32   0.000     .2772282    .5267102
                _cons |   2.843276   .0838641    33.90   0.000     2.678855    3.007696
---------------------------------------------------------------------------------------
(est4 stored)

. estimates store react

. coefplot threat confidence moral react, keep(treatment_reassurance treatment_abandon treatment_conditional treatment_domestic trea
> tment_normative treatment_shaming) ///
> recast(bar) barw(0.15) vertical ylab(0(.1).7) ///
> ciopts(recast(rcap) color(black%50)) citop ///
> legend(order(1 "Threat Perception" 3 "Distrust of US" ///
> 5 "Moral Obligation" 7 "Reactance")) ///
> ytitle("Treatment Effects") ///
> xtitle("Treatment Condition") xsc(titlegap(2) outergap(0))  ///
> xlabel(1 "Reassure" 2 "Abandon" 3 "Conditional" 4 "Domestic" 5 "Obligations" 6 "Shaming") ytick(-1(0.2)1) ylabel(-1(0.2)1) graphre
> gion(fcolor(white)) yline(0, lpattern(dash) lstyle(foreground) lcolor(black)) scheme(white_tableau)

. *graph export "Figure3.jpg", replace
. eststo clear

. restore

. 
. 
. 
. 
. 
. ***APPENDIX***
. 
. *Table A1*
. sutex2 defensespend control treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative a
> ge female education polawareness, varlabels minmax
%------- Begin LaTeX code -------%
\begin{table}[htbp]\centering \caption{Summary statistics\label{sumstat}}
\begin{tabular}{l c c c c c }\hline\hline
\multicolumn{1}{c}{Variable} & Obs & Mean & Std. Dev.
 & Min & Max  \\ \hline
Defense spending & 3985 & 3.564 & 1.139 & 1 & 5  \\
Control Condition & 3985 & .155 & .362 & 0 & 1  \\
Treatment: Unconditional Reassurance & 3985 & .152 & .359 & 0 & 1  \\
Treatment: Unconditional Abandonment & 3985 & .152 & .359 & 0 & 1  \\
Treatment: Conditional Pressure & 3985 & .155 & .362 & 0 & 1  \\
Treatment: Domestic Pressure & 3985 & .154 & .361 & 0 & 1  \\
Treatment: Appeal to Obligations & 3985 & .154 & .361 & 0 & 1  \\
Age & 3985 & 46.53 & 15.778 & 18 & 86  \\
Female & 3985 & .501 & .5 & 0 & 1  \\
Education & 3985 & 3.653 & 1.458 & 1 & 6  \\
Political Awareness & 3985 & 3.195 & .888 & 1 & 4  \\
\hline
\end{tabular}
\end{table}
%------- End LaTeX code -------%

. 
. sutex2 defensespend control treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative a
> ge female education polawareness if country=="Poland", varlabels minmax
%------- Begin LaTeX code -------%
\begin{table}[htbp]\centering \caption{Summary statistics\label{sumstat}}
\begin{tabular}{l c c c c c }\hline\hline
\multicolumn{1}{c}{Variable} & Obs & Mean & Std. Dev.
 & Min & Max  \\ \hline
Defense spending & 1848 & 3.635 & 1.208 & 1 & 5  \\
Control Condition & 1848 & .167 & .373 & 0 & 1  \\
Treatment: Unconditional Reassurance & 1848 & .165 & .371 & 0 & 1  \\
Treatment: Unconditional Abandonment & 1848 & .166 & .372 & 0 & 1  \\
Treatment: Conditional Pressure & 1848 & .169 & .375 & 0 & 1  \\
Treatment: Domestic Pressure & 1848 & .168 & .374 & 0 & 1  \\
Treatment: Appeal to Obligations & 1848 & .166 & .372 & 0 & 1  \\
Age & 1848 & 45.17 & 15.72 & 18 & 86  \\
Female & 1848 & .503 & .5 & 0 & 1  \\
Education & 1848 & 3.769 & 1.491 & 1 & 6  \\
Political Awareness & 1848 & 3.06 & .958 & 1 & 4  \\
\hline
\end{tabular}
\end{table}
%------- End LaTeX code -------%

. 
. sutex2 defensespend control treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative t
> reatment_shaming age female education polawareness if country=="Germany", varlabels minmax
%------- Begin LaTeX code -------%
\begin{table}[htbp]\centering \caption{Summary statistics\label{sumstat}}
\begin{tabular}{l c c c c c }\hline\hline
\multicolumn{1}{c}{Variable} & Obs & Mean & Std. Dev.
 & Min & Max  \\ \hline
Defense spending & 2137 & 3.502 & 1.072 & 1 & 5  \\
Control Condition & 2137 & .146 & .353 & 0 & 1  \\
Treatment: Unconditional Reassurance & 2137 & .142 & .349 & 0 & 1  \\
Treatment: Unconditional Abandonment & 2137 & .14 & .347 & 0 & 1  \\
Treatment: Conditional Pressure & 2137 & .143 & .35 & 0 & 1  \\
Treatment: Domestic Pressure & 2137 & .141 & .348 & 0 & 1  \\
Treatment: Appeal to Obligations & 2137 & .144 & .351 & 0 & 1  \\
Treatment: Shaming & 2137 & .144 & .351 & 0 & 1  \\
Age & 2137 & 47.706 & 15.737 & 18 & 86  \\
Female & 2137 & .5 & .5 & 0 & 1  \\
Education & 2137 & 3.553 & 1.422 & 1 & 6  \\
Political Awareness & 2137 & 3.313 & .805 & 1 & 4  \\
\hline
\end{tabular}
\end{table}
%------- End LaTeX code -------%

. 
. 
. *Table A2*
. eststo clear

. eststo: reg age treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatment_sha
> ming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      3.96
       Model |  6867.24093         7  981.034419   Prob > F        =    0.0003
    Residual |  984925.365     3,977   247.65536   R-squared       =    0.0069
-------------+----------------------------------   Adj R-squared   =    0.0052
       Total |  991792.606     3,984  248.943927   Root MSE        =    15.737

---------------------------------------------------------------------------------------
                  age |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .7737278   .8989389     0.86   0.389    -.9886965    2.536152
    treatment_abandon |   .7244057   .8993199     0.81   0.421    -1.038766    2.487577
treatment_conditional |   .6041506   .8948969     0.68   0.500    -1.150349     2.35865
   treatment_domestic |   -.195112   .8967277    -0.22   0.828    -1.953201    1.562977
  treatment_normative |   .3550999   .8963473     0.40   0.692    -1.402243    2.112443
    treatment_shaming |   .5253522   1.127329     0.47   0.641    -1.684845     2.73555
           country_id |   2.513994   .5190662     4.84   0.000     1.496333    3.531655
                _cons |   44.79507   .6841793    65.47   0.000     43.45369    46.13644
---------------------------------------------------------------------------------------
(est1 stored)

. eststo: reg female treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatment_
> shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      0.28
       Model |  .488269363         7  .069752766   Prob > F        =    0.9625
    Residual |  995.756649     3,977  .250378841   R-squared       =    0.0005
-------------+----------------------------------   Adj R-squared   =   -0.0013
       Total |  996.244918     3,984  .250061476   Root MSE        =    .50038

---------------------------------------------------------------------------------------
               female |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0030581   .0285828    -0.11   0.915    -.0590965    .0529802
    treatment_abandon |   .0010787   .0285949     0.04   0.970    -.0549834    .0571408
treatment_conditional |  -.0088863   .0284543    -0.31   0.755    -.0646727    .0469001
   treatment_domestic |  -.0276222   .0285125    -0.97   0.333    -.0835227    .0282783
  treatment_normative |  -.0202617   .0285004    -0.71   0.477    -.0761385    .0356151
    treatment_shaming |  -.0246789   .0358448    -0.69   0.491    -.0949547    .0455969
           country_id |   -.000853   .0165043    -0.05   0.959    -.0332107    .0315047
                _cons |   .5125449   .0217543    23.56   0.000     .4698943    .5551955
---------------------------------------------------------------------------------------
(est2 stored)

. eststo: reg education treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatme
> nt_shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      4.67
       Model |   68.987978         7  9.85542543   Prob > F        =    0.0000
    Residual |  8400.03988     3,977  2.11215486   R-squared       =    0.0081
-------------+----------------------------------   Adj R-squared   =    0.0064
       Total |  8469.02785     3,984     2.12576   Root MSE        =    1.4533

---------------------------------------------------------------------------------------
            education |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0917229   .0830174    -1.10   0.269    -.2544836    .0710378
    treatment_abandon |   -.182345   .0830526    -2.20   0.028    -.3451746   -.0195153
treatment_conditional |  -.1234143   .0826441    -1.49   0.135    -.2854431    .0386145
   treatment_domestic |  -.0929036   .0828132    -1.12   0.262    -.2552639    .0694567
  treatment_normative |   .0526387   .0827781     0.64   0.525    -.1096528    .2149301
    treatment_shaming |  -.0351345   .1041094    -0.34   0.736    -.2392472    .1689782
           country_id |  -.2223977    .047936    -4.64   0.000    -.3163791   -.1284163
                _cons |   3.841948   .0631843    60.81   0.000     3.718071    3.965824
---------------------------------------------------------------------------------------
(est3 stored)

. eststo: reg generaltrust treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =     15.31
       Model |  22.2915584         7  3.18450835   Prob > F        =    0.0000
    Residual |  827.293385     3,977  .208019458   R-squared       =    0.0262
-------------+----------------------------------   Adj R-squared   =    0.0245
       Total |  849.584944     3,984  .213249233   Root MSE        =    .45609

---------------------------------------------------------------------------------------
         generaltrust |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0037245    .026053    -0.14   0.886    -.0548031     .047354
    treatment_abandon |  -.0010406   .0260641    -0.04   0.968    -.0521408    .0500596
treatment_conditional |    .006316   .0259359     0.24   0.808    -.0445329    .0571648
   treatment_domestic |   .0563659   .0259889     2.17   0.030      .005413    .1073188
  treatment_normative |   .0075717   .0259779     0.29   0.771    -.0433596     .058503
    treatment_shaming |   .0552239   .0326722     1.69   0.091     -.008832    .1192798
           country_id |    .136537   .0150436     9.08   0.000     .1070432    .1660308
                _cons |   .2205767   .0198289    11.12   0.000      .181701    .2594524
---------------------------------------------------------------------------------------
(est4 stored)

. eststo: reg internationaltrust treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normativ
> e treatment_shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =     12.18
       Model |  19.2843929         7  2.75491327   Prob > F        =    0.0000
    Residual |  899.251115     3,977  .226112928   R-squared       =    0.0210
-------------+----------------------------------   Adj R-squared   =    0.0193
       Total |  918.535508     3,984  .230556101   Root MSE        =    .47551

---------------------------------------------------------------------------------------
   internationaltrust |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0223585   .0271625    -0.82   0.410    -.0756121    .0308952
    treatment_abandon |  -.0213156    .027174    -0.78   0.433    -.0745918    .0319606
treatment_conditional |  -.0066361   .0270403    -0.25   0.806    -.0596502    .0463781
   treatment_domestic |   .0421299   .0270956     1.55   0.120    -.0109928    .0952525
  treatment_normative |   .0291966   .0270841     1.08   0.281    -.0239035    .0822967
    treatment_shaming |   .0512449   .0340635     1.50   0.133    -.0155387    .1180285
           country_id |   .1222809   .0156842     7.80   0.000     .0915312    .1530307
                _cons |   .2875131   .0206733    13.91   0.000      .246982    .3280443
---------------------------------------------------------------------------------------
(est5 stored)

. eststo: reg usconfidence treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      4.25
       Model |  35.6734427         7  5.09620609   Prob > F        =    0.0001
    Residual |  4768.76671     3,977  1.19908642   R-squared       =    0.0074
-------------+----------------------------------   Adj R-squared   =    0.0057
       Total |  4804.44015     3,984  1.20593377   Root MSE        =     1.095

---------------------------------------------------------------------------------------
         usconfidence |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0454145   .0625506     0.73   0.468    -.0772197    .1680488
    treatment_abandon |   .0871088   .0625771     1.39   0.164    -.0355775     .209795
treatment_conditional |   .0737618   .0622694     1.18   0.236     -.048321    .1958447
   treatment_domestic |   .0631192   .0623968     1.01   0.312    -.0592134    .1854518
  treatment_normative |   .0408913   .0623703     0.66   0.512    -.0813894     .163172
    treatment_shaming |   .0545356   .0784426     0.70   0.487     -.099256    .2083271
           country_id |   .1817516    .036118     5.03   0.000       .11094    .2525632
                _cons |    2.67605   .0476071    56.21   0.000     2.582714    2.769387
---------------------------------------------------------------------------------------
(est6 stored)

. eststo: reg defenseguess2 treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative tre
> atment_shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =     38.11
       Model |   143.40878         7  20.4869686   Prob > F        =    0.0000
    Residual |  2138.06023     3,977  .537606293   R-squared       =    0.0629
-------------+----------------------------------   Adj R-squared   =    0.0612
       Total |  2281.46901     3,984  .572657884   Root MSE        =    .73322

---------------------------------------------------------------------------------------
        defenseguess2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0527044   .0418831     1.26   0.208    -.0294099    .1348187
    treatment_abandon |   .0694025   .0419008     1.66   0.098    -.0127466    .1515516
treatment_conditional |   .0410002   .0416947     0.98   0.325    -.0407449    .1227452
   treatment_domestic |   .0320965     .04178     0.77   0.442    -.0498158    .1140088
  treatment_normative |  -.0108517   .0417623    -0.26   0.795    -.0927293    .0710259
    treatment_shaming |  -.0413416   .0525242    -0.79   0.431    -.1443184    .0616352
           country_id |  -.3641227   .0241842   -15.06   0.000    -.4115373   -.3167082
                _cons |   2.158711   .0318771    67.72   0.000     2.096214    2.221208
---------------------------------------------------------------------------------------
(est7 stored)

. eststo: reg polawareness treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming country_id 

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =     12.24
       Model |  66.3061818         7  9.47231168   Prob > F        =    0.0000
    Residual |  3077.80323     3,977  .773900736   R-squared       =    0.0211
-------------+----------------------------------   Adj R-squared   =    0.0194
       Total |  3144.10941     3,984  .789184089   Root MSE        =    .87972

---------------------------------------------------------------------------------------
         polawareness |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0122601   .0502515     0.24   0.807     -.086261    .1107812
    treatment_abandon |   .0036604   .0502728     0.07   0.942    -.0949024    .1022233
treatment_conditional |   .0441219   .0500255     0.88   0.378    -.0539562       .1422
   treatment_domestic |   -.002531   .0501279    -0.05   0.960    -.1008098    .0957477
  treatment_normative |   .0605556   .0501066     1.21   0.227    -.0376815    .1587926
    treatment_shaming |   .0718178   .0630187     1.14   0.255    -.0517342    .1953698
           country_id |   .2455072   .0290163     8.46   0.000     .1886191    .3023954
                _cons |   3.039818   .0382462    79.48   0.000     2.964834    3.114802
---------------------------------------------------------------------------------------
(est8 stored)

. eststo clear

. 
. *Table A3*
. eststo clear

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      4.86
       Model |  43.8146422         7  6.25923461   Prob > F        =    0.0000
    Residual |  5124.30932     3,977  1.28848613   R-squared       =    0.0085
-------------+----------------------------------   Adj R-squared   =    0.0067
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1351

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .1012542   .0648405     1.56   0.118    -.0258695    .2283779
    treatment_abandon |   .1660634    .064868     2.56   0.011     .0388858    .2932409
treatment_conditional |    .237753   .0645489     3.68   0.000     .1112009    .3643051
   treatment_domestic |   .0263072    .064681     0.41   0.684    -.1005038    .1531182
  treatment_normative |   .0622068   .0646535     0.96   0.336    -.0645504     .188964
    treatment_shaming |   .0202447   .0813143     0.25   0.803    -.1391769    .1796662
           country_id |  -.1208644   .0374403    -3.23   0.001    -.1942683   -.0474606
                _cons |   3.535685   .0493499    71.65   0.000     3.438931    3.632438
---------------------------------------------------------------------------------------
(est1 stored)

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative if c
> ountry=="Poland"

      Source |       SS           df       MS      Number of obs   =     1,848
-------------+----------------------------------   F(5, 1842)      =      2.02
       Model |  14.6837122         5  2.93674244   Prob > F        =    0.0732
    Residual |  2679.76596     1,842  1.45481323   R-squared       =    0.0054
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  2694.44968     1,847  1.45882495   Root MSE        =    1.2062

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0531442    .097514     0.54   0.586    -.1381055    .2443939
    treatment_abandon |   .1767252   .0973535     1.82   0.070    -.0142097    .3676601
treatment_conditional |   .2527056   .0968828     2.61   0.009     .0626939    .4427173
   treatment_domestic |   .0526788   .0969602     0.54   0.587    -.1374846    .2428422
  treatment_normative |   .0375862    .097274     0.39   0.699    -.1531926     .228365
                _cons |   3.538961   .0687271    51.49   0.000      3.40417    3.673752
---------------------------------------------------------------------------------------
(est2 stored)

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming if country=="Germany"

      Source |       SS           df       MS      Number of obs   =     2,137
-------------+----------------------------------   F(6, 2130)      =      2.05
       Model |  14.0919544         6  2.34865906   Prob > F        =    0.0563
    Residual |  2442.14857     2,130  1.14654862   R-squared       =    0.0057
-------------+----------------------------------   Adj R-squared   =    0.0029
       Total |  2456.24052     2,136  1.14992534   Root MSE        =    1.0708

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .1494805   .0864329     1.73   0.084    -.0200211    .3189822
    treatment_abandon |   .1550911   .0866515     1.79   0.074    -.0148393    .3250215
treatment_conditional |   .2224114    .086218     2.58   0.010     .0533311    .3914916
   treatment_domestic |  -.0009795   .0865053    -0.01   0.991    -.1706232    .1686642
  treatment_normative |   .0867958   .0861472     1.01   0.314    -.0821456    .2557372
    treatment_shaming |   .0234894   .0860768     0.27   0.785    -.1453139    .1922927
                _cons |   3.411576   .0607178    56.19   0.000     3.292503    3.530648
---------------------------------------------------------------------------------------
(est3 stored)

. eststo clear

. 
. *Table A4*
. eststo clear

. eststo: reg defensespend i.treatment_reassurance##c.threatperception_pretreat i.treatment_abandon##c.threatperception_pretreat i.t
> reatment_conditional##c.threatperception_pretreat i.treatment_domestic##c.threatperception_pretreat i.treatment_normative##c.threa
> tperception_pretreat i.treatment_shaming##c.threatperception_pretreat country_id
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity
note: threatperception_pretreat omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(14, 3970)     =      3.25
       Model |  58.6015739        14  4.18582671   Prob > F        =    0.0000
    Residual |  5109.52239     3,970  1.28703335   R-squared       =    0.0113
-------------+----------------------------------   Adj R-squared   =    0.0079
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1345

-------------------------------------------------------------------------------------------------------------------
                                     defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------------------------------------+----------------------------------------------------------------
                          1.treatment_reassurance |  -.1950163   .2476341    -0.79   0.431    -.6805182    .2904855
                        threatperception_pretreat |  -.0774645   .0553478    -1.40   0.162    -.1859772    .0310483
                                                  |
treatment_reassurance#c.threatperception_pretreat |
                                               1  |   .0991634   .0802553     1.24   0.217    -.0581821    .2565088
                                                  |
                              1.treatment_abandon |  -.1883606   .2526456    -0.75   0.456    -.6836879    .3069667
                        threatperception_pretreat |          0  (omitted)
                                                  |
    treatment_abandon#c.threatperception_pretreat |
                                               1  |   .1177865   .0809032     1.46   0.146    -.0408293    .2764022
                                                  |
                          1.treatment_conditional |  -.1442579   .2399763    -0.60   0.548    -.6147463    .3262306
                        threatperception_pretreat |          0  (omitted)
                                                  |
treatment_conditional#c.threatperception_pretreat |
                                               1  |   .1272903   .0769582     1.65   0.098    -.0235911    .2781716
                                                  |
                             1.treatment_domestic |  -.4945334   .2488902    -1.99   0.047    -.9824981   -.0065688
                        threatperception_pretreat |          0  (omitted)
                                                  |
   treatment_domestic#c.threatperception_pretreat |
                                               1  |   .1752677   .0808365     2.17   0.030     .0167828    .3337526
                                                  |
                            1.treatment_normative |  -.3057545   .2379304    -1.29   0.199    -.7722316    .1607227
                        threatperception_pretreat |          0  (omitted)
                                                  |
  treatment_normative#c.threatperception_pretreat |
                                               1  |   .1226416   .0762739     1.61   0.108     -.026898    .2721813
                                                  |
                              1.treatment_shaming |   .2292917   .2755754     0.83   0.405    -.3109908    .7695743
                        threatperception_pretreat |          0  (omitted)
                                                  |
    treatment_shaming#c.threatperception_pretreat |
                                               1  |  -.0872791   .0940134    -0.93   0.353    -.2715983      .09704
                                                  |
                                       country_id |  -.1086129   .0388378    -2.80   0.005    -.1847567   -.0324691
                                            _cons |   3.761547   .1751194    21.48   0.000     3.418215     4.10488
-------------------------------------------------------------------------------------------------------------------
(est1 stored)

. eststo: reg defensespend i.treatment_reassurance##c.usconfidence i.treatment_abandon##c.usconfidence i.treatment_conditional##c.us
> confidence i.treatment_domestic##c.usconfidence i.treatment_normative##c.usconfidence i.treatment_shaming##c.usconfidence country_
> id
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity
note: usconfidence omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(14, 3970)     =     15.98
       Model |   275.63673        14  19.6883378   Prob > F        =    0.0000
    Residual |  4892.48724     3,970  1.23236454   R-squared       =    0.0533
-------------+----------------------------------   Adj R-squared   =    0.0500
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1101

------------------------------------------------------------------------------------------------------
                        defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------------+----------------------------------------------------------------
             1.treatment_reassurance |   .0144103   .1752641     0.08   0.934    -.3292059    .3580265
                        usconfidence |   .2087186   .0408266     5.11   0.000     .1286755    .2887616
                                     |
treatment_reassurance#c.usconfidence |
                                  1  |   .0275097    .058552     0.47   0.638    -.0872852    .1423046
                                     |
                 1.treatment_abandon |   .2120162   .1771001     1.20   0.231    -.1351996     .559232
                        usconfidence |          0  (omitted)
                                     |
    treatment_abandon#c.usconfidence |
                                  1  |  -.0224805   .0587944    -0.38   0.702    -.1377506    .0927897
                                     |
             1.treatment_conditional |   .2925263   .1718152     1.70   0.089    -.0443281    .6293807
                        usconfidence |          0  (omitted)
                                     |
treatment_conditional#c.usconfidence |
                                  1  |   -.024711    .057012    -0.43   0.665    -.1364866    .0870646
                                     |
                1.treatment_domestic |  -.1125065   .1763546    -0.64   0.524    -.4582607    .2332476
                        usconfidence |          0  (omitted)
                                     |
   treatment_domestic#c.usconfidence |
                                  1  |   .0444132   .0588076     0.76   0.450    -.0708827     .159709
                                     |
               1.treatment_normative |  -.0688187   .1713958    -0.40   0.688    -.4048507    .2672133
                        usconfidence |          0  (omitted)
                                     |
  treatment_normative#c.usconfidence |
                                  1  |   .0436242   .0571554     0.76   0.445    -.0684326     .155681
                                     |
                 1.treatment_shaming |   .0145873   .2075674     0.07   0.944    -.3923615     .421536
                        usconfidence |          0  (omitted)
                                     |
    treatment_shaming#c.usconfidence |
                                  1  |  -.0018333   .0669057    -0.03   0.978    -.1330059    .1293394
                                     |
                          country_id |  -.1595754   .0367682    -4.34   0.000    -.2316616   -.0874891
                               _cons |   2.977533   .1222002    24.37   0.000     2.737952    3.217114
------------------------------------------------------------------------------------------------------
(est2 stored)

. eststo clear

. 
. *Table A5*
. eststo clear

. eststo: reg threatperception treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative 
> treatment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      2.54
       Model |  21.2863156         7  3.04090223   Prob > F        =    0.0131
    Residual |  4756.49637     3,977   1.1960011   R-squared       =    0.0045
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  4777.78269     3,984  1.19924264   Root MSE        =    1.0936

---------------------------------------------------------------------------------------
     threatperception |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0424974   .0624701    -0.68   0.496    -.1649738     .079979
    treatment_abandon |   .1438111   .0624966     2.30   0.021     .0212828    .2663394
treatment_conditional |   .0567936   .0621892     0.91   0.361    -.0651321    .1787193
   treatment_domestic |   .0146566   .0623164     0.24   0.814    -.1075186    .1368317
  treatment_normative |   .0144723     .06229     0.23   0.816     -.107651    .1365956
    treatment_shaming |  -.1204236   .0783417    -1.54   0.124    -.2740171      .03317
           country_id |   .0764884   .0360715     2.12   0.034      .005768    .1472088
                _cons |   2.716013   .0475458    57.12   0.000     2.622797    2.809229
---------------------------------------------------------------------------------------
(est1 stored)

. eststo: reg confidence_us treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative tre
> atment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      8.33
       Model |   69.016613         7  9.85951615   Prob > F        =    0.0000
    Residual |  4708.71388     3,977  1.18398639   R-squared       =    0.0144
-------------+----------------------------------   Adj R-squared   =    0.0127
       Total |  4777.73049     3,984  1.19922954   Root MSE        =    1.0881

---------------------------------------------------------------------------------------
        confidence_us |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |  -.0085119   .0621555    -0.14   0.891    -.1303715    .1133478
    treatment_abandon |   .2813273   .0621819     4.52   0.000      .159416    .4032386
treatment_conditional |   .0992943    .061876     1.60   0.109    -.0220175     .220606
   treatment_domestic |   .1699815   .0620026     2.74   0.006     .0484216    .2915414
  treatment_normative |   .0111316   .0619763     0.18   0.857    -.1103767      .13264
    treatment_shaming |  -.0129176   .0779472    -0.17   0.868    -.1657377    .1399026
           country_id |  -.1435976   .0358899    -4.00   0.000    -.2139619   -.0732333
                _cons |    3.08184   .0473063    65.15   0.000     2.989093    3.174587
---------------------------------------------------------------------------------------
(est2 stored)

. eststo: reg moralobligation treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative t
> reatment_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =      5.81
       Model |   15.520742         7  2.21724886   Prob > F        =    0.0000
    Residual |  1518.89231     3,977  .381919112   R-squared       =    0.0101
-------------+----------------------------------   Adj R-squared   =    0.0084
       Total |  1534.41305     3,984  .385143838   Root MSE        =      .618

---------------------------------------------------------------------------------------
      moralobligation |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0858488   .0353014     2.43   0.015     .0166383    .1550594
    treatment_abandon |   -.028828   .0353164    -0.82   0.414    -.0980679    .0404119
treatment_conditional |   .0270238   .0351427     0.77   0.442    -.0418756    .0959231
   treatment_domestic |   .0163244   .0352146     0.46   0.643    -.0527159    .0853647
  treatment_normative |   .0265573   .0351996     0.75   0.451    -.0424538    .0955683
    treatment_shaming |   .0571263   .0442703     1.29   0.197    -.0296684    .1439209
           country_id |   -.109649   .0203838    -5.38   0.000    -.1496126   -.0696854
                _cons |   2.248951   .0268678    83.70   0.000     2.196275    2.301627
---------------------------------------------------------------------------------------
(est3 stored)

. eststo: reg reactance treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative treatme
> nt_shaming country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(7, 3977)      =     18.03
       Model |   469.52506         7  67.0750086   Prob > F        =    0.0000
    Residual |  14798.4339     3,977  3.72100425   R-squared       =    0.0308
-------------+----------------------------------   Adj R-squared   =    0.0290
       Total |   15267.959     3,984  3.83231902   Root MSE        =     1.929

---------------------------------------------------------------------------------------
            reactance |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0796294   .1101885     0.72   0.470    -.1364019    .2956607
    treatment_abandon |   .7935384   .1102352     7.20   0.000     .5774155    1.009661
treatment_conditional |   .3711216   .1096931     3.38   0.001     .1560616    .5861815
   treatment_domestic |   .5679892   .1099175     5.17   0.000     .3524893    .7834891
  treatment_normative |   .0331014   .1098709     0.30   0.763    -.1823071    .2485099
    treatment_shaming |   .0956643   .1381838     0.69   0.489    -.1752533     .366582
           country_id |   .4019692   .0636252     6.32   0.000     .2772282    .5267102
                _cons |   2.843276   .0838641    33.90   0.000     2.678855    3.007696
---------------------------------------------------------------------------------------
(est4 stored)

. eststo clear

. 
. *Table A6*
. eststo clear

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming female age education polawareness country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(11, 3973)     =     19.89
       Model |  269.773438        11   24.524858   Prob > F        =    0.0000
    Residual |  4898.35053     3,973  1.23290977   R-squared       =    0.0522
-------------+----------------------------------   Adj R-squared   =    0.0496
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1104

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0916998   .0634415     1.45   0.148    -.0326812    .2160808
    treatment_abandon |   .1589662   .0634956     2.50   0.012     .0344792    .2834532
treatment_conditional |   .2255226   .0631694     3.57   0.000     .1016751    .3493702
   treatment_domestic |   .0290492   .0632892     0.46   0.646    -.0950332    .1531316
  treatment_normative |   .0489205   .0632601     0.77   0.439    -.0751048    .1729458
    treatment_shaming |   .0040179   .0795598     0.05   0.960     -.151964    .1599998
               female |  -.0132117   .0354497    -0.37   0.709     -.082713    .0562896
                  age |   .0107929   .0011645     9.27   0.000     .0085098     .013076
            education |    .006804   .0123053     0.55   0.580    -.0173213    .0309293
         polawareness |   .1457816   .0210766     6.92   0.000     .1044597    .1871035
           country_id |  -.1822863   .0371309    -4.91   0.000    -.2550836   -.1094889
                _cons |   2.589697   .0993107    26.08   0.000     2.394992    2.784402
---------------------------------------------------------------------------------------
(est1 stored)

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming defenseguess2 militarism female age education polawareness catholic protestant country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(15, 3969)     =     25.04
       Model |   446.87244        15   29.791496   Prob > F        =    0.0000
    Residual |  4721.25152     3,969  1.18953175   R-squared       =    0.0865
-------------+----------------------------------   Adj R-squared   =    0.0830
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.0907

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0987226   .0623396     1.58   0.113    -.0234981    .2209433
    treatment_abandon |   .1536133   .0624393     2.46   0.014     .0311971    .2760295
treatment_conditional |   .2259659   .0620635     3.64   0.000     .1042865    .3476453
   treatment_domestic |   .0245982   .0621852     0.40   0.692    -.0973196    .1465161
  treatment_normative |   .0338117   .0621583     0.54   0.586    -.0880536     .155677
    treatment_shaming |  -.0178086   .0782204    -0.23   0.820    -.1711644    .1355473
        defenseguess2 |  -.2119352    .023691    -8.95   0.000    -.2583828   -.1654875
           militarism |   .1519787   .0196017     7.75   0.000     .1135484    .1904089
               female |  -.0086113   .0351746    -0.24   0.807    -.0775733    .0603507
                  age |   .0111487   .0011461     9.73   0.000     .0089017    .0133956
            education |   .0121404   .0121123     1.00   0.316    -.0116064    .0358873
         polawareness |   .1330099   .0207783     6.40   0.000     .0922726    .1737471
             catholic |   .1079835    .042939     2.51   0.012     .0237989    .1921682
           protestant |   .1273283   .0521651     2.44   0.015     .0250554    .2296013
           country_id |  -.2763125   .0435417    -6.35   0.000    -.3616787   -.1909463
                _cons |   2.638204    .121988    21.63   0.000     2.399039     2.87737
---------------------------------------------------------------------------------------
(est2 stored)

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative defe
> nseguess2 militarism female age education polawareness catholic protestant i.party_poland if country=="Poland"

      Source |       SS           df       MS      Number of obs   =     1,848
-------------+----------------------------------   F(17, 1830)     =      4.54
       Model |  109.087334        17  6.41690203   Prob > F        =    0.0000
    Residual |  2585.36234     1,830  1.41276631   R-squared       =    0.0405
-------------+----------------------------------   Adj R-squared   =    0.0316
       Total |  2694.44968     1,847  1.45882495   Root MSE        =    1.1886

----------------------------------------------------------------------------------------------
                defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
       treatment_reassurance |   .0698012   .0963929     0.72   0.469    -.1192504    .2588529
           treatment_abandon |   .1864167   .0961762     1.94   0.053      -.00221    .3750434
       treatment_conditional |   .2590814   .0955881     2.71   0.007     .0716083    .4465546
          treatment_domestic |   .0694961    .095914     0.72   0.469    -.1186162    .2576085
         treatment_normative |   .0346677   .0960314     0.36   0.718     -.153675    .2230104
               defenseguess2 |  -.0177763   .0392489    -0.45   0.651    -.0947537    .0592011
                  militarism |   .0293495   .0312383     0.94   0.348     -.031917    .0906161
                      female |   .0495959   .0576388     0.86   0.390    -.0634489    .1626407
                         age |   .0099874   .0018527     5.39   0.000     .0063537    .0136211
                   education |   .0284855   .0191079     1.49   0.136    -.0089901     .065961
                polawareness |   .1092592    .031048     3.52   0.000      .048366    .1701525
                    catholic |   .0709167   .0722838     0.98   0.327    -.0708508    .2126842
                  protestant |  -.0492768   .1842391    -0.27   0.789    -.4106178    .3120641
                             |
                party_poland |
      Law and Justice (PiS)  |     -.0586   .0697376    -0.84   0.401    -.1953736    .0781736
              New Left (NL)  |   .0324226   .0976865     0.33   0.740    -.1591662    .2240113
                      Other  |   .0079777   .0847928     0.09   0.925    -.1583232    .1742786
Polish People's Party (PSL)  |  -.1320807   .1308872    -1.01   0.313    -.3887846    .1246232
                             |
                       _cons |   2.555814   .1861079    13.73   0.000     2.190808     2.92082
----------------------------------------------------------------------------------------------
(est3 stored)

. eststo: reg defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative trea
> tment_shaming defenseguess2 militarism female age education polawareness catholic protestant i.party_germany if country=="Germany"

      Source |       SS           df       MS      Number of obs   =     2,137
-------------+----------------------------------   F(21, 2115)     =     21.45
       Model |  431.310347        21  20.5385879   Prob > F        =    0.0000
    Residual |  2024.93018     2,115  .957413795   R-squared       =    0.1756
-------------+----------------------------------   Adj R-squared   =    0.1674
       Total |  2456.24052     2,136  1.14992534   Root MSE        =    .97848

--------------------------------------------------------------------------------------------------------------------
                                      defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------------------------+----------------------------------------------------------------
                             treatment_reassurance |   .1173585   .0794196     1.48   0.140    -.0383902    .2731073
                                 treatment_abandon |   .1276784   .0797009     1.60   0.109     -.028622    .2839788
                             treatment_conditional |   .1842949   .0790638     2.33   0.020     .0292439    .3393459
                                treatment_domestic |    .005618   .0792164     0.07   0.943    -.1497321    .1609682
                               treatment_normative |   .0425626   .0790905     0.54   0.591    -.1125408    .1976659
                                 treatment_shaming |  -.0445234   .0789497    -0.56   0.573    -.1993505    .1103038
                                     defenseguess2 |   -.339787   .0300579   -11.30   0.000    -.3987331    -.280841
                                        militarism |   .2293955   .0250758     9.15   0.000     .1802197    .2785713
                                            female |  -.0027648    .043717    -0.06   0.950    -.0884977     .082968
                                               age |   .0100348    .001447     6.93   0.000     .0071971    .0128725
                                         education |  -.0090039   .0154991    -0.58   0.561    -.0393988    .0213911
                                      polawareness |   .1285501   .0283474     4.53   0.000     .0729584    .1841417
                                          catholic |   .0743699    .054202     1.37   0.170    -.0319248    .1806647
                                        protestant |   .1232908    .051306     2.40   0.016     .0226753    .2239063
                                                   |
                                     party_germany |
                    Alternative for Germany (AfD)  |  -.1941805   .0844421    -2.30   0.022    -.3597788   -.0285822
Christian Democratic Union Party of Germany (CDU)  |  -.0645909   .0776542    -0.83   0.406    -.2168775    .0876956
          Christian Social Union in Bavaria (CSU)  |   .0295994   .1169695     0.25   0.800    -.1997878    .2589866
                      Free Democratic Party (FDP)  |  -.1277757    .095028    -1.34   0.179    -.3141337    .0585824
                                            Other  |  -.2478483   .1032145    -2.40   0.016    -.4502608   -.0454358
         Social Democratic Party of Germany (SPD)  |  -.1447991   .0744179    -1.95   0.052    -.2907391    .0011409
                                 The Left (LINKE)  |  -.2519653   .0964952    -2.61   0.009    -.4412008   -.0627299
                                                   |
                                             _cons |      2.691   .1751711    15.36   0.000     2.347474    3.034526
--------------------------------------------------------------------------------------------------------------------
(est4 stored)

. eststo clear

. 
. *Table A7*
. eststo clear

. eststo: ologit defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative t
> reatment_shaming country_id

Iteration 0:   log likelihood = -5841.5167  
Iteration 1:   log likelihood = -5818.4046  
Iteration 2:   log likelihood = -5818.3868  
Iteration 3:   log likelihood = -5818.3868  

Ordered logistic regression                     Number of obs     =      3,985
                                                LR chi2(7)        =      46.26
                                                Prob > chi2       =     0.0000
Log likelihood = -5818.3868                     Pseudo R2         =     0.0040

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .1361405   .1019842     1.33   0.182    -.0637448    .3360259
    treatment_abandon |   .2703831   .1035272     2.61   0.009     .0674734    .4732927
treatment_conditional |   .3675084   .1016377     3.62   0.000     .1683021    .5667147
   treatment_domestic |   .0544649   .1028111     0.53   0.596    -.1470412     .255971
  treatment_normative |   .0939642   .1019924     0.92   0.357    -.1059373    .2938657
    treatment_shaming |    .033054   .1251812     0.26   0.792    -.2122967    .2784046
           country_id |  -.2807158   .0597812    -4.70   0.000    -.3978848   -.1635469
----------------------+----------------------------------------------------------------
                /cut1 |  -2.679072    .096824                     -2.868844   -2.489301
                /cut2 |  -1.631062   .0844923                     -1.796664    -1.46546
                /cut3 |  -.2986765   .0795917                     -.4546735   -.1426796
                /cut4 |   1.224253   .0816408                       1.06424    1.384266
---------------------------------------------------------------------------------------
(est1 stored)

. eststo: ologit defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative i
> f country=="Poland"

Iteration 0:   log likelihood = -2739.9958  
Iteration 1:   log likelihood = -2734.7668  
Iteration 2:   log likelihood = -2734.7651  
Iteration 3:   log likelihood = -2734.7651  

Ordered logistic regression                     Number of obs     =      1,848
                                                LR chi2(5)        =      10.46
                                                Prob > chi2       =     0.0632
Log likelihood = -2734.7651                     Pseudo R2         =     0.0019

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .0460602   .1431612     0.32   0.748    -.2345305    .3266509
    treatment_abandon |   .2817762   .1457357     1.93   0.053    -.0038606     .567413
treatment_conditional |   .3603014   .1430751     2.52   0.012     .0798794    .6407235
   treatment_domestic |   .0840971   .1434452     0.59   0.558    -.1970503    .3652444
  treatment_normative |   .0438643    .143323     0.31   0.760    -.2370435    .3247722
----------------------+----------------------------------------------------------------
                /cut1 |  -2.387749   .1268696                     -2.636409   -2.139089
                /cut2 |    -1.3729   .1095192                     -1.587554   -1.158247
                /cut3 |   -.311533   .1028857                     -.5131853   -.1098808
                /cut4 |   1.072908    .105384                      .8663595    1.279457
---------------------------------------------------------------------------------------
(est2 stored)

. eststo: ologit defensespend treatment_reassurance treatment_abandon treatment_conditional treatment_domestic treatment_normative t
> reatment_shaming if country=="Germany"

Iteration 0:   log likelihood = -3055.0446  
Iteration 1:   log likelihood = -3048.9934  
Iteration 2:   log likelihood =  -3048.991  
Iteration 3:   log likelihood =  -3048.991  

Ordered logistic regression                     Number of obs     =      2,137
                                                LR chi2(6)        =      12.11
                                                Prob > chi2       =     0.0596
Log likelihood =  -3048.991                     Pseudo R2         =     0.0020

---------------------------------------------------------------------------------------
         defensespend |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
treatment_reassurance |   .2541338   .1452171     1.75   0.080    -.0304865    .5387542
    treatment_abandon |     .27534   .1471313     1.87   0.061     -.013032    .5637121
treatment_conditional |   .3924315   .1445527     2.71   0.007     .1091133    .6757497
   treatment_domestic |   .0298668   .1473966     0.20   0.839    -.2590253    .3187588
  treatment_normative |   .1649382   .1451513     1.14   0.256    -.1195532    .4494296
    treatment_shaming |   .0570631   .1439044     0.40   0.692    -.2249843    .3391105
----------------------+----------------------------------------------------------------
                /cut1 |  -2.628146   .1308845                     -2.884675   -2.371617
                /cut2 |  -1.539023   .1104645                      -1.75553   -1.322517
                /cut3 |   .0259059   .1036139                     -.1771737    .2289855
                /cut4 |   1.695081   .1109457                      1.477632    1.912531
---------------------------------------------------------------------------------------
(est3 stored)

. eststo clear

. 
. *Figure A1a*
. preserve

. eststo clear

. reg defensespend i.treatment_reassurance##i.prosocial i.treatment_abandon##i.prosocial i.treatment_conditional##i.prosocial i.trea
> tment_domestic##i.prosocial i.treatment_normative##i.prosocial i.treatment_shaming##i.prosocial country_id

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(14, 3970)     =      3.18
       Model |   57.399176        14  4.09994114   Prob > F        =    0.0001
    Residual |  5110.72479     3,970  1.28733622   R-squared       =    0.0111
-------------+----------------------------------   Adj R-squared   =    0.0076
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1346

-------------------------------------------------------------------------------------------------
                   defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------------------+----------------------------------------------------------------
        1.treatment_reassurance |   .0924254   .0907411     1.02   0.308    -.0854782     .270329
                                |
                      prosocial |
                     Prosocial  |   .0612761   .0912221     0.67   0.502    -.1175705    .2401227
                                |
treatment_reassurance#prosocial |
                   1#Prosocial  |   .0239154   .1297742     0.18   0.854    -.2305149    .2783457
                                |
            1.treatment_abandon |   .1498897   .0918866     1.63   0.103    -.0302596    .3300389
                                |
    treatment_abandon#prosocial |
                   1#Prosocial  |   .0343284   .1297044     0.26   0.791    -.2199651    .2886218
                                |
        1.treatment_conditional |   .1987518   .0891323     2.23   0.026     .0240025    .3735012
                                |
treatment_conditional#prosocial |
                   1#Prosocial  |   .0987124    .129546     0.76   0.446    -.1552705    .3526954
                                |
           1.treatment_domestic |  -.0029276   .0893767    -0.03   0.974     -.178156    .1723009
                                |
   treatment_domestic#prosocial |
                   1#Prosocial  |   .0758116   .1297799     0.58   0.559    -.1786299    .3302532
                                |
          1.treatment_normative |    .035466   .0892632     0.40   0.691      -.13954    .2104719
                                |
  treatment_normative#prosocial |
                   1#Prosocial  |   .0709151    .129796     0.55   0.585    -.1835581    .3253882
                                |
            1.treatment_shaming |   .0015347   .1083398     0.01   0.989    -.2108722    .2139415
                                |
    treatment_shaming#prosocial |
                   1#Prosocial  |   .0632031   .1597831     0.40   0.692    -.2500617    .3764678
                                |
                     country_id |  -.1245605    .037469    -3.32   0.001    -.1980208   -.0511002
                          _cons |   3.506359   .0677174    51.78   0.000     3.373595    3.639123
-------------------------------------------------------------------------------------------------

. eststo M

. listcoef, help //returns the coeficients; "help listcoef" to learn 

regress (N=3985): Unstandardized and Standardized Estimates 

 Observed SD: 1.1389556
 SD of Error: 1.1346084

---------------------------------------------------------------------------
defensespend|      b         t     P>|t|    bStdX    bStdY   bStdXY      SDofX
---------+-----------------------------------------------------------------
1.treatment_reassurance|   0.09243    1.019   0.308   0.0332   0.0811   0.0292     0.3594
1.prosocial|   0.06128    0.672   0.502   0.0305   0.0538   0.0268     0.4986
1.treatment_reassurance#1.prosocial|   0.02392    0.184   0.854   0.0062   0.0210   0.0054     0.2577
1.treatment_abandon|   0.14989    1.631   0.103   0.0538   0.1316   0.0473     0.3591
1.treatment_abandon#1.prosocial|   0.03433    0.265   0.791   0.0091   0.0301   0.0080     0.2639
1.treatment_conditional|   0.19875    2.230   0.026   0.0720   0.1745   0.0632     0.3620
1.treatment_conditional#1.prosocial|   0.09871    0.762   0.446   0.0249   0.0867   0.0218     0.2518
1.treatment_domestic|  -0.00293   -0.033   0.974  -0.0011  -0.0026  -0.0009     0.3608
1.treatment_domestic#1.prosocial|   0.07581    0.584   0.559   0.0191   0.0666   0.0167     0.2514
1.treatment_normative|   0.03547    0.397   0.691   0.0128   0.0311   0.0112     0.3611
1.treatment_normative#1.prosocial|   0.07092    0.546   0.585   0.0178   0.0623   0.0156     0.2509
1.treatment_shaming|   0.00153    0.014   0.989   0.0004   0.0013   0.0004     0.2671
1.treatment_shaming#1.prosocial|   0.06320    0.396   0.692   0.0111   0.0555   0.0098     0.1763
country_id|  -0.12456   -3.324   0.001  -0.0621  -0.1094  -0.0545     0.4987
---------------------------------------------------------------------------
       b = raw coefficient
       t = t-score for test of b=0
   P>|t| = p-value for t-test
   bStdX = x-standardized coefficient
   bStdY = y-standardized coefficient
  bStdXY = fully standardized coefficient
   SDofX = standard deviation of X

. //now the margins
. estimates restore M
(results M are active now)

. margins, dydx(treatment_reassurance) at(prosocial=(0(1)1)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_reassurance

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               prosocial       =           0
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               prosocial       =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_reassurance  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_reassurance  |
                     _at |
                      1  |   .0924254  _b[1.treatment_reassurance:1bn._at]
                      2  |   .1163408  _b[1.treatment_reassurance:2._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store reassurance

. estimates restore M
(results M are active now)

. margins, dydx(treatment_normative) at(prosocial=(0(1)1)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_normative

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               prosocial       =           0
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               prosocial       =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

----------------------------------------------------------------------------------------
                       |      dy/dx  Legend
-----------------------+----------------------------------------------------------------
0.treatment_normative  |  (base outcome)
-----------------------+----------------------------------------------------------------
1.treatment_normative  |
                   _at |
                    1  |    .035466  _b[1.treatment_normative:1bn._at]
                    2  |    .106381  _b[1.treatment_normative:2._at]
----------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store normative

. estimates restore M
(results M are active now)

. margins, dydx(treatment_shaming) at(prosocial=(0(1)1)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_shaming

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               prosocial       =           0
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               prosocial       =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

--------------------------------------------------------------------------------------
                     |      dy/dx  Legend
---------------------+----------------------------------------------------------------
0.treatment_shaming  |  (base outcome)
---------------------+----------------------------------------------------------------
1.treatment_shaming  |
                 _at |
                  1  |   .0015347  _b[1.treatment_shaming:1bn._at]
                  2  |   .0647377  _b[1.treatment_shaming:2._at]
--------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store shaming

. 
. coefplot reassurance (normative, mcolor(purple) mfcolor(purple) bcolor(purple) blcolor(black)) (shaming, mcolor(brown) mfcolor(bro
> wn) bcolor(brown) blcolor(black)), ///
> recast(bar) barw(0.15) vertical ylab(0(.1).7) ///
> ciopts(recast(rcap) color(black%50)) citop ///
> legend(order(1 "Reassurance" 3 "Appeal to Obligations" ///
> 5 "Shaming")) ///
> ytitle("Treatment Effects") ///
> xtitle("Prosocial")  ///
> xlabel(1 "Not prosocial" 2 "Prosocial") ytick(-1(0.2)1) ylabel(-1(0.2)1) graphregion(fcolor(white)) yline(0, lpattern(dash) lstyle
> (foreground) lcolor(black)) scheme(white_tableau)

. eststo clear

. restore

. 
. 
. *Figure A1b*
. preserve

. eststo clear

. reg defensespend i.treatment_reassurance##c.nationalism i.treatment_abandon##c.nationalism i.treatment_conditional##c.nationalism 
> i.treatment_domestic##c.nationalism i.treatment_normative##c.nationalism i.treatment_shaming##c.nationalism country_id
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     3,985
-------------+----------------------------------   F(14, 3970)     =      3.28
       Model |  59.1750949        14  4.22679249   Prob > F        =    0.0000
    Residual |  5108.94887     3,970  1.28688888   R-squared       =    0.0115
-------------+----------------------------------   Adj R-squared   =    0.0080
       Total |  5168.12396     3,984  1.29721987   Root MSE        =    1.1344

-----------------------------------------------------------------------------------------------------
                       defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------------------+----------------------------------------------------------------
            1.treatment_reassurance |  -.4096738    .312709    -1.31   0.190    -1.022759    .2034115
                        nationalism |  -.0710092    .060673    -1.17   0.242    -.1899624    .0479439
                                    |
treatment_reassurance#c.nationalism |
                                 1  |   .1517517   .0908812     1.67   0.095    -.0264265      .32993
                                    |
                1.treatment_abandon |  -.3373905   .2993801    -1.13   0.260    -.9243436    .2495626
                        nationalism |          0  (omitted)
                                    |
    treatment_abandon#c.nationalism |
                                 1  |   .1483268   .0861041     1.72   0.085    -.0204856    .3171393
                                    |
            1.treatment_conditional |   -.413293   .3029822    -1.36   0.173    -1.007308    .1807223
                        nationalism |          0  (omitted)
                                    |
treatment_conditional#c.nationalism |
                                 1  |   .1916544   .0871858     2.20   0.028     .0207214    .3625875
                                    |
               1.treatment_domestic |   -.038481   .3001241    -0.13   0.898    -.6268929    .5499308
                        nationalism |          0  (omitted)
                                    |
   treatment_domestic#c.nationalism |
                                 1  |   .0192373   .0864896     0.22   0.824    -.1503309    .1888055
                                    |
              1.treatment_normative |  -.4359302   .2966716    -1.47   0.142    -1.017573    .1457128
                        nationalism |          0  (omitted)
                                    |
  treatment_normative#c.nationalism |
                                 1  |   .1481359   .0860849     1.72   0.085    -.0206389    .3169106
                                    |
                1.treatment_shaming |   .1664878   .3775886     0.44   0.659     -.573798    .9067736
                        nationalism |          0  (omitted)
                                    |
    treatment_shaming#c.nationalism |
                                 1  |  -.0513217   .1134777    -0.45   0.651    -.2738017    .1711583
                                    |
                         country_id |  -.1106905   .0381186    -2.90   0.004    -.1854243   -.0359567
                              _cons |   3.771018   .2126439    17.73   0.000     3.354116    4.187919
-----------------------------------------------------------------------------------------------------

. eststo M

. reg defensespend i.treatment_reassurance##c.nationalism i.treatment_abandon##c.nationalism i.treatment_conditional##c.nationalism 
> i.treatment_domestic##c.nationalism i.treatment_normative##c.nationalism i.treatment_shaming##c.nationalism if country=="Germany"
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity
note: nationalism omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     2,137
-------------+----------------------------------   F(13, 2123)     =      1.56
       Model |  23.2715163        13  1.79011664   Prob > F        =    0.0889
    Residual |  2432.96901     2,123  1.14600519   R-squared       =    0.0095
-------------+----------------------------------   Adj R-squared   =    0.0034
       Total |  2456.24052     2,136  1.14992534   Root MSE        =    1.0705

-----------------------------------------------------------------------------------------------------
                       defensespend |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------------------+----------------------------------------------------------------
            1.treatment_reassurance |   .2411415   .4152368     0.58   0.561    -.5731719    1.055455
                        nationalism |    .039996   .0824616     0.49   0.628    -.1217179    .2017099
                                    |
treatment_reassurance#c.nationalism |
                                 1  |  -.0278502   .1264188    -0.22   0.826    -.2757678    .2200675
                                    |
                1.treatment_abandon |  -.1279639   .3922033    -0.33   0.744    -.8971067     .641179
                        nationalism |          0  (omitted)
                                    |
    treatment_abandon#c.nationalism |
                                 1  |   .0873134   .1176298     0.74   0.458    -.1433682     .317995
                                    |
            1.treatment_conditional |  -.1485897   .4105668    -0.36   0.717    -.9537448    .6565654
                        nationalism |          0  (omitted)
                                    |
treatment_conditional#c.nationalism |
                                 1  |   .1094592    .121287     0.90   0.367    -.1283946    .3473131
                                    |
               1.treatment_domestic |   .1021894   .4025639     0.25   0.800    -.6872714    .8916502
                        nationalism |          0  (omitted)
                                    |
   treatment_domestic#c.nationalism |
                                 1  |  -.0317324    .120252    -0.26   0.792    -.2675565    .2040916
                                    |
              1.treatment_normative |  -.0214593   .3886944    -0.06   0.956    -.7837208    .7408023
                        nationalism |          0  (omitted)
                                    |
  treatment_normative#c.nationalism |
                                 1  |    .035472   .1181491     0.30   0.764     -.196228    .2671721
                                    |
                1.treatment_shaming |    .545516   .4043915     1.35   0.177    -.2475289    1.338561
                        nationalism |          0  (omitted)
                                    |
    treatment_shaming#c.nationalism |
                                 1  |  -.1623269   .1224302    -1.33   0.185    -.4024225    .0777687
                                    |
                              _cons |   3.281299   .2753709    11.92   0.000     2.741274    3.821324
-----------------------------------------------------------------------------------------------------

. eststo K

. listcoef, help //returns the coeficients; "help listcoef" to learn 

regress (N=2137): Unstandardized and Standardized Estimates 

 Observed SD: 1.0723457
 SD of Error: 1.0705163

---------------------------------------------------------------------------
defensespend|      b         t     P>|t|    bStdX    bStdY   bStdXY      SDofX
---------+-----------------------------------------------------------------
1.treatment_reassurance|   0.24114    0.581   0.561   0.0841   0.2249   0.0785     0.3489
nationalism|   0.04000    0.485   0.628   0.0282   0.0373   0.0263     0.7040
1.treatment_reassurance#c.nationalism|  -0.02785   -0.220   0.826  -0.0316  -0.0260  -0.0295     1.1353
1.treatment_abandon|  -0.12796   -0.326   0.744  -0.0445  -0.1193  -0.0415     0.3475
1.treatment_abandon#c.nationalism|   0.08731    0.742   0.458   0.1014   0.0814   0.0946     1.1614
1.treatment_conditional|  -0.14859   -0.362   0.717  -0.0521  -0.1386  -0.0485     0.3503
1.treatment_conditional#c.nationalism|   0.10946    0.902   0.367   0.1317   0.1021   0.1229     1.2036
1.treatment_domestic|   0.10219    0.254   0.800   0.0356   0.0953   0.0332     0.3484
1.treatment_domestic#c.nationalism|  -0.03173   -0.264   0.792  -0.0372  -0.0296  -0.0347     1.1732
1.treatment_normative|  -0.02146   -0.055   0.956  -0.0075  -0.0200  -0.0070     0.3508
1.treatment_normative#c.nationalism|   0.03547    0.300   0.764   0.0405   0.0331   0.0378     1.1421
1.treatment_shaming|   0.54552    1.349   0.177   0.1916   0.5087   0.1787     0.3513
1.treatment_shaming#c.nationalism|  -0.16233   -1.326   0.185  -0.1873  -0.1514  -0.1746     1.1537
---------------------------------------------------------------------------
       b = raw coefficient
       t = t-score for test of b=0
   P>|t| = p-value for t-test
   bStdX = x-standardized coefficient
   bStdY = y-standardized coefficient
  bStdXY = fully standardized coefficient
   SDofX = standard deviation of X

. //now the margins
. estimates restore M
(results M are active now)

. margins, dydx(treatment_domestic) at(nationalism=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_domestic

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

---------------------------------------------------------------------------------------
                      |      dy/dx  Legend
----------------------+----------------------------------------------------------------
0.treatment_domestic  |  (base outcome)
----------------------+----------------------------------------------------------------
1.treatment_domestic  |
                  _at |
                   1  |  -.0192437  _b[1.treatment_domestic:1bn._at]
                   2  |  -6.43e-06  _b[1.treatment_domestic:2._at]
                   3  |   .0192309  _b[1.treatment_domestic:3._at]
                   4  |   .0384682  _b[1.treatment_domestic:4._at]
                   5  |   .0577055  _b[1.treatment_domestic:5._at]
---------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store domestic

. estimates restore M
(results M are active now)

. margins, dydx(treatment_abandon) at(nationalism=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_abandon

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

--------------------------------------------------------------------------------------
                     |      dy/dx  Legend
---------------------+----------------------------------------------------------------
0.treatment_abandon  |  (base outcome)
---------------------+----------------------------------------------------------------
1.treatment_abandon  |
                 _at |
                  1  |  -.1890636  _b[1.treatment_abandon:1bn._at]
                  2  |  -.0407368  _b[1.treatment_abandon:2._at]
                  3  |   .1075901  _b[1.treatment_abandon:3._at]
                  4  |   .2559169  _b[1.treatment_abandon:4._at]
                  5  |   .4042437  _b[1.treatment_abandon:5._at]
--------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store abandon

. estimates restore M
(results M are active now)

. margins, dydx(treatment_conditional) at(nationalism=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_conditional

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_conditional  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_conditional  |
                     _at |
                      1  |  -.2216386  _b[1.treatment_conditional:1bn._at]
                      2  |  -.0299842  _b[1.treatment_conditional:2._at]
                      3  |   .1616703  _b[1.treatment_conditional:3._at]
                      4  |   .3533247  _b[1.treatment_conditional:4._at]
                      5  |   .5449792  _b[1.treatment_conditional:5._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store conditional

. est restore M
(results M are active now)

. margins, dydx(treatment_reassurance) at(nationalism=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_reassurance

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

------------------------------------------------------------------------------------------
                         |      dy/dx  Legend
-------------------------+----------------------------------------------------------------
0.treatment_reassurance  |  (base outcome)
-------------------------+----------------------------------------------------------------
1.treatment_reassurance  |
                     _at |
                      1  |  -.2579221  _b[1.treatment_reassurance:1bn._at]
                      2  |  -.1061703  _b[1.treatment_reassurance:2._at]
                      3  |   .0455814  _b[1.treatment_reassurance:3._at]
                      4  |   .1973331  _b[1.treatment_reassurance:4._at]
                      5  |   .3490849  _b[1.treatment_reassurance:5._at]
------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store reassurance

. est restore M
(results M are active now)

. margins, dydx(treatment_normative) at(nationalism=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_normative

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

----------------------------------------------------------------------------------------
                       |      dy/dx  Legend
-----------------------+----------------------------------------------------------------
0.treatment_normative  |  (base outcome)
-----------------------+----------------------------------------------------------------
1.treatment_normative  |
                   _at |
                    1  |  -.2877944  _b[1.treatment_normative:1bn._at]
                    2  |  -.1396585  _b[1.treatment_normative:2._at]
                    3  |   .0084774  _b[1.treatment_normative:3._at]
                    4  |   .1566132  _b[1.treatment_normative:4._at]
                    5  |   .3047491  _b[1.treatment_normative:5._at]
----------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store normative

. est restore M
(results M are active now)

. margins, dydx(treatment_shaming) at(nationalism=(1(1)5)) atmeans predict(xb) coeflegend post

Conditional marginal effects                    Number of obs     =      3,985
Model VCE    : OLS

Expression   : Linear prediction, predict(xb)
dy/dx w.r.t. : 1.treatment_shaming

1._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           1
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

2._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           2
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

3._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           3
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

4._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           4
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

5._at        : 0.treatme~ce    =    .8476788 (mean)
               1.treatme~ce    =    .1523212 (mean)
               nationalism     =           5
               0.treatmen~n    =    .8479297 (mean)
               1.treatmen~n    =    .1520703 (mean)
               0.treatmen~l    =    .8449184 (mean)
               1.treatmen~l    =    .1550816 (mean)
               0.treatmen~c    =    .8461731 (mean)
               1.treatmen~c    =    .1538269 (mean)
               0.treatme~ve    =    .8459222 (mean)
               1.treatme~ve    =    .1540778 (mean)
               0.treatmen~g    =    .9227102 (mean)
               1.treatmen~g    =    .0772898 (mean)
               country_id      =     .536261 (mean)

--------------------------------------------------------------------------------------
                     |      dy/dx  Legend
---------------------+----------------------------------------------------------------
0.treatment_shaming  |  (base outcome)
---------------------+----------------------------------------------------------------
1.treatment_shaming  |
                 _at |
                  1  |   .1151661  _b[1.treatment_shaming:1bn._at]
                  2  |   .0638444  _b[1.treatment_shaming:2._at]
                  3  |   .0125227  _b[1.treatment_shaming:3._at]
                  4  |   -.038799  _b[1.treatment_shaming:4._at]
                  5  |  -.0901207  _b[1.treatment_shaming:5._at]
--------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est store shaming

. 
. coefplot reassurance abandon conditional domestic (normative, bcolor(purple) mlcolor(black) blcolor(black)) (shaming, bcolor(brown
> ) mlcolor(black) blcolor(black)), ///
> recast(bar) barw(0.15) vertical ylab(0(.1).7) ///
> ciopts(recast(rcap) color(black%50)) citop ///
> legend(order(1 "Reassurance" 3 "Abandonment" ///
> 5 "Conditional Pressure" 7 "Domestic Pressure" 9 "Appeal to Obligations" 11 "Shaming")) ///
> ytitle("Treatment Effects") ///
> xtitle("Nationalism")  ///
> xlabel(1(1)5) ytick(-1(0.2)1) ylabel(-1(0.2)1) graphregion(fcolor(white)) yline(0, lpattern(dash) lstyle(foreground) lcolor(black)
> ) scheme(white_tableau)

. eststo clear

. restore

. 
end of do-file

. log close
      name:  <unnamed>
       log:  C:\Users\brdbl\Dropbox\New Alliance Work\Burden-Sharing Survey\Submissions\Final Versions\Replication Package\Replicati
> on_LogFile.log
  log type:  text
 closed on:  22 Nov 2023, 15:01:54
------------------------------------------------------------------------------------------------------------------------------------
